This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more. Our labs give you hands-on experience with these machine learning and data science concepts. You will develop concrete machine learning skills as well as create a final project demonstrating your proficiency.

Machine Learning Introduction for Everyone

Machine Learning Introduction for Everyone


Instructors: Aije Egwaikhide
31,905 already enrolled
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312 reviews
What you'll learn
Compare and contrast artificial intelligence, machine learning, and deep learning
Explain the machine learning models development lifecycle
Differentiate between supervised and unsupervised machine learning
Evaluate classification models using metrics such as accuracy, confusion matrices, precision, and recall
Skills you'll gain
- Deep Learning
- Applied Machine Learning
- Predictive Modeling
- Artificial Intelligence
- Model Evaluation
- Machine Learning Methods
- Supervised Learning
- Model Training
- Reinforcement Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Regression Analysis
- Unsupervised Learning
- Machine Learning Algorithms
- Machine Learning
Tools you'll learn
Details to know

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There are 3 modules in this course
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Reviewed on Jun 12, 2022
Very informative and for someone who just knows the word "Machine Learning", this was a good learning curve in getting to know about it
Reviewed on Jun 4, 2025
It's a great time and experience to learn machine learning
Reviewed on Apr 1, 2023
A fantastic course for beginners to have a clear-cut idea !
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